1. Field of the Invention
This invention relates to signal processing arrangements, and more particularly to such arrangements which are adapted for use with time varying band-limited input signals, such as speech.
2. Description of the Related Art
For a number of years the time encoding of speech and other time varying band-limited signals has been known, as a means for the economical coding of time varying signals into a plurality of Time Encoded Speech or Signal (TES) descriptors or symbols to afford a TES symbol stream, and for forming such a symbol stream into fixed dimensional, fixed size data matrices, where the dimensionality and size of the matrix is fixed, a priori, by design, irrespective of the duration of the input speech or other event to be recognized. See, for example:
1. U.K. Patent No. 2145864 and corresponding European Patent No. 0141497. PA0 2. Article by J. Holbeche, R. D. Hughes, and R. A. King, "Time Encoded Speech (TES) descriptors as a symbol feature set for voice recognition systems", published in IEE Int. Conf. Speech Input/Output; Techniques and Applications, pages 310-315, London, March 1986. PA0 3. Article by Martin George "A New Approach to Speaker Verification", published in "VOICE +", October 1995, Vol. 2, No. 8. PA0 4. U.K. Patent No. 2268609 and corresponding International Application No. PCT/GB92/00285 (WO92/00285). PA0 5. Article by Martin George "Time for TESPAR" published in "CONDITION MONITOR", September 1995, No. 105.
The time encoding of speech and other signals described in the above references have, for convenience, been referred to as TESPAR coding, where TESPAR stands for Time Encoded Signal Processing and Recognition.
It should be appreciated that references in this document to Time Encoded Speech, or Time Encoded Signals, or TES, are intended to indicate solely, the concepts and processes of time encoding, set out in the aforesaid references and not to any other processes.
In U.K. Patent No. 2145864 and in some of the other references already referred to, it is described in detail how a speech waveform, which may typically be an individual word or a group of words, may be coded using time encoded speech (TES) coding, in the form of a stream of TES symbols, and also how the symbol stream may be coded in the form of, for example, an "A" matrix, which is of fixed size regardless of the length of the speech waveform.
As has already been mentioned and as is described in others of the references referred to, it has been appreciated that the principle of TES coding is applicable to any time varying band-limited signal ranging from seismic signals with frequencies and bandwidths of fractions of a Hertz, to radio frequency signals in the gigaHertz region and beyond. One particularly important application is in the evaluation of acoustic and vibrational emissions from rotating machinery.
In the references referred to it has been shown that time varying input signals may be represented in TESPAR matrix form where the matrix may typically be one dimensional or two dimensional. For the purposes of this disclosure two dimensional or "A" matrices will be used but the processes are identical with "N" dimensional matrices where "N" may be any number greater than 1, and typically between 1 and 3. It has also been shown how numbers of "A" matrices purporting to represent a particular word, or person, or condition, may be grouped together simply to form archetypes, that is to say archetype matrices, such that those events which are consistent in the set are enhanced and those which are inconsistent and variable, are reduced in significance. It is then possible to compare an "A" matrix derived from an input signal being investigated with the archetype matrices in order to provide an indication of the identification or verification of the input signal. In this respect see U.K. Patent No. 2268609 (Reference 4) in which the comparison of the input matrix with the archetype matrices is carried out using fast artificial neural networks (FANN's). It will be appreciated, as is explained in the prior art, for time varying waveforms especially, this process is several orders of magnitude simpler and more effective than similar processes deployed utilizing conventional procedures and frequency domain data sets.
It has now been appreciated that the performance of TESPAR and TESPAR/FANN recognition and classification and discrimination systems can, nevertheless, be further significantly improved.